Part Three – The Digital Revolution (Part Twelve)

Economic Unit

Artificial Intelligence
Introduction: Definitions and Applications

Artificial Intelligence (AI) is a comprehensive term that includes natural language processing, machine learning, deep learning, computer vision, robotics, and other logic- and reasoning-based algorithms.

Some AI technologies have the potential to replicate or even exceed the capabilities required by humans. These capabilities include:

• Learning and adaptation

• Sensory perception and interaction

• Reasoning and planning

• Search and optimization

• Autonomy and creativity

Much of the public discussion and media coverage of AI focuses on the risks of advanced models. The UK government defines these models as “highly capable general-purpose AI models that can perform a wide range of tasks and possess abilities equal to or exceeding the most advanced existing models.”

These risks include:

• Hallucinations: apparently logical but incorrect responses

• Reduced reliability in performing long-term tasks

• Presence of biases

• Lack of precise contextual information

Additionally, the discussion around generative AI has increased; a specific type of AI capable of producing and interpreting high-quality outputs, including text and images.

This report examines how businesses use AI and how to increase productivity safely and securely.

In conversations with businesses and experts, multiple examples were observed where AI improved efficiency and productivity, contributing to a competitive advantage. For example, in computer science, AI helps find solutions to programming problems, boosting productivity.

Other examples cited by businesses include:

• A small marketing company using AI to analyze and categorize large volumes of text.

• A small hospitality company using AI to draft letters and social media posts.

However, there is still a need for skilled users to interpret and implement the results. AI can also perform other economically useful tasks (with varying degrees of success), such as:

• Multilingual translation

• Smooth conversation

• Summarization of long documents

In a broader view, AI growth is expected to be initially driven by model training infrastructures, then move toward inference devices for large language models, digital advertising, specialized software, services, and the integration of AI technology into business applications.

Bloomberg estimates that the generative AI market will grow to $1.3 trillion globally over the next ten years, compared with about $40 billion in 2022.

Applications of AI
The Future of Privacy Forum, which aims to increase public understanding of AI, has provided examples of AI applications across sectors to demonstrate how AI will be used in the future:

Finance

• Tax compliance programs: applications that assist in completing tax forms and ensure that information is provided legally and in accordance with tax regulations.